Method and Apparatus for measuring Distortion Product Otoacoustic Emissions (DPOAE) by means of frequency modulated stimuli

ABSTRACT

A method to reduce DPOAE fine structure in the measurement of DPOAE acoustic signals generated in the cochlea in response to two primary tones.

BACKGROUND OF THE INVENTION

1. Field

This invention relates to measurement of Distortion Product OtoacousticEmissions (DPOAE), acoustic signals generated in the cochlea. Inparticular, it relates to a method to reduce DPOAE fine structure byusing frequency modulated primary tones.

2. State of the Art

The mammal and human ear features an amplification system, whichamplifies soft sound by up to 40 dB. This “cochlear amplifier” employsso-called outer hair cells (OHC) located in the organ of Corti in theinner ear. The mechanical activity of the OHC is non-linear, causingnon-linear distortion to be produced in the inner ear.

The non-linearity of the ear has been known over a century, but it wasrelatively recent that the OHC of the cochlea were identified as theprimary cause. The middle ear is quite linear over sound pressures of 40to 110 dB SPL, and does not result in noticeable distortion at normallistening levels. The inner ear non-linearity does produce distortion,which can be heard, and measured in the ear canal. Measurement ofdistortion products in the ear canal is used as a hearing test fornewborn infants, since the distortion products are absent for certainforms of hearing impairment.

In principle the ear non-linearity could be expressed as a power series;that is, where the response is linearly proportional to the soundpressure, plus a term proportional to the square of the sound pressure,cube of the pressure, etc. If two frequencies were present, a squareterm would produce intermodulation products equal to the sum anddifference of the two frequencies. A cubic term would produce productsequal to twice one frequency plus and minus the other frequency.

If continuous sinusoidal sounds are applied as a stimulus, the soundresponse generated by the inner ear can be separated from the stimulusby analysing the outside sound response generated frequencies of thestimuli. Since intermodulation products of the primary frequencies aregenerated as a result of the non-linearity of the functioning inner ear,the presence of signals whose frequencies do not match (“clash”) withthe stimulus signals is a deciding factor in proving the integrity ofthe inner ear. These signals are termed distortion product otoacousticemissions (DPOAE).

DPOAE are acoustic signals, generated in the cochlea of mammals,especially humans, as a response of two sine tones of differentfrequency (“primary tones”) used as stimuli. The probe for recordingDPOAE typically contains two loudspeakers for stimulation and one ormore microphones for recording.

Typically, primary tones with levels L₁, L₂ and frequencies f₂ are setwith f₁<f₂ and L₁≧L₂ and the frequency ratio f₂/f₁ is in the order of1.2 to 1.3.

The strongest DPOAE component is generated at f_(DPOAE)=2*f₁−f₂. Thiscomponent is the one used by virtually all commercial DPOAE equipment.

DPOAE measurements work in a broad frequency range, from less then 500Hz to more than 10 kHz, depending on the subject, recording equipment,and noise conditions.

DPOAE are thought to be generated by the so-called “outer hair cells”,which act as an acoustic amplifier in the cochlea.

Since the DPOAE are only a side effect of this cochlear amplifier, thesignal that can be recorded in the ear canal is normally small inamplitude, compared to background noise and stimuli. This makes signalprocessing necessary to detect the signal combined with backgroundnoise.

DPOAE Detection

The common method to detect DPOAE is framing the measurement of raw datain frames of constant length, with all frequencies (f₁, f₂, f_(DPOAE)being multiples of the frame rate).

The frames or the FFT components of the frames are usually averaged withsome artifact rejection scheme to finally decide a DPOAE has been foundor to determine its amplitude.

A widely used method to decide a DPOAE has been recorded is to observethe amplitude of the recorded spectrum at f_(DPOAE) compared to theneighboring frequency components (“SNR criterion”).

In order to support the stimuli described below, DPOAE detection needsto be designed differently, to allow small, continuous frequencydeviations.

DPOAE Fine Structure

When measuring DPOAE with a high frequency resolution, such as onemeasurement every 20 Hz, fine structure can be observed in mostsubjects. Fine structure in this context means, that the amplitude ofDPOAE varies with frequency, and can show variations of up to 20 dBwithin as little as 100 Hz primary tone frequency modification. Thisfine structure is thought to be the result of outer hair cells in theregions that are tuned to the DPOAE frequency that generate otoacousticemissions (OAE) themselves, which can constructively or destructivelyinterfere with the original source, located at the overlap region of theprimary tones f₁ and f₂.

The main aspects of DPOAE fine structure are outlined in the article,“Separation Anxiety: DPOAE Components Refuse to be Apart”, by SumitDhar, www.otoemissions.org/guest_editorials/2009/dhar/2009.htm.

An example of such a recording, ranging from 2 kHz to 4 kHz with 20 Hzresolution, is shown in FIG. 1. Three recordings were performed to provethe reproducibility of the fine structure.

DPOAE fine structure is unwanted in many applications of DPOAEmeasurements. In newborn hearing screening, test time is crucial.Hitting a fine structure minimum with one or more of the testfrequencies can extend test time dramatically, or lead to refer results.Typically 4 to 6 frequencies are tested, with an “overall criterion”that passes a subject if, for example, DPOAE are found at 3 of the 4frequencies.

When using DPOAE to estimate the hearing threshold, usually byextrapolating input-output functions, the fine structure, because it islevel dependent, can severely corrupt the growth behavior at certainfrequencies. This leads to large errors in estimating the hearingthreshold.

In both cases, there is no need to measure exactly using only nominalstimulus frequencies. Deviations in the order of +100 Hz are tolerablefor most applications. This is supported by the common DPOAE model,which predicts a certain region of the cochlea producing the DPOAEresponse. This region is thought to be close to the location tuned tof₂, and covers a frequency range anyway.

In many applications, it is even desirable to cover a frequency bandwith a single DPOAE measurement instead of a single frequency, sinceoften only a few tests at selected frequencies can be done in reasonabletime, which are then used to characterize performance of hearing overthe complete frequency range. Typically, test frequencies are spaced ascoarse as octaves of half-octaves.

In order to overcome unwanted effects of the DPOAE fine structure, it isdesirable to disable or attenuate the so-called second source. Methodshave been suggested to mask the second source with additional stimulustones, for example a tone that is close to f_(DPOAE).

However, these methods do not perform as stable as desired, and usefulparameter settings vary strongly among subjects. The method describedbelow provides a new approach for measuring DPOAE.

SUMMARY OF THE INVENTION

Frequency Modulated Stimuli

The invention comprises a method for measuring DPOAE by means offrequency-modulated stimuli that compensate for the fine structureeffects, hereinafter referred to as FMDPOAE. The method for measuringDPOAE by means of frequency modulated stimuli comprises exposing asubject to an incoming signal comprised of two primary tones to elicitDPOAE responses, which are then recorded. The modified stimulus (FMmodulated primary tones) makes the inner ear “produce” DPOAE withoutfine structure. That means the fine structure is not suppressed at therecoding part of the system, but at the generator (the cochlea) itself.Hence, statistics are not part of an artefact rejection scheme to rejector influence unwanted fine structure. Instead, the fine structure isavoided by use of modified stimulus.

DPOAE fine structure is also reported to interfere with the measurementof DPOAE suppression when applying contralateral masking,www.ncbi.nlm.nig.gov/pubmed/18537382. The use of frequency-modulatedstimuli can reduce this effect and therefore allow better accuracy andreproducibility of such measurements. That is, if you apply maskingsound to the left ear and look for level changes of the DPOAE in theright ear, or vice versa.

To detect the frequency modulated DPOAE signals, various analyticalmethods, such as quadrature demodulation can be used. Quadraturedemodulation makes use of Cartesian coordinates, x and y. Whenconsidering quadrature modulation, the x-axis is called the I (in-phase)axis, and the y-axis is called the Q (quadrature) axis.

At least one of the primary tones is modulated in frequency, generallyresulting in a frequency modulated DPOAE signal.

The method of measuring DPOAE is particularly used for newborn hearingscreening where the patient does not understand how to respond to thestimuli. It is also used for diagnostic DPOAE measurements.

The statistical methodology used to reject environmental noise artifactscomprises weighted averaging, one-tailed, two-tailed, and hypothesistesting, or other suitable analytical methods.

One preferred method for measuring DPOAE includes calculating the I andQ components of the quadrature signal by multiplying the incoming (rawor pre-filtered) signal with appropriate sine and cosine functions. Thismethod is also referred to as quadrature demodulation. The I and Q datais then independently windowed and framed before averaging the I and Qsignals. The averaged I/Q vector is then statistically evaluated todetect a statistically significant DPAOAE signal and/or estimate itsamplitude.

There are two possible explanations of how this can reduce finestructure. One explanation is that the DPOAE output of neighboringfrequencies are just “averaged” by shifting forth and back the stimulusfrequencies. A different explanation is that the Second source may betoo slow to follow the constantly changing f_(DPOAE).

The frequency modulation itself can be done in many different schemes,which will perform differently in achieving the goal of suppressing theSecond source without reducing the DPOAE output of the First source toomuch.

Special attention has to be taken to the phase of the DPOAE signal,which can hinder a proper averaging or similar signal detection scheme.The detection algorithm needs to be “aware” of the current expectedphase of the DPOAE response to make sure the signal is detectedcorrectly.

One modulation scheme would be to shift both primary tones by atime-varying frequency shift, which would shift f_(DPOAE) by the sameabsolute amount:

f ₁ =f _(1BASE) +f(t)

f ₂ =f _(2BASE) +f(t)

f _(DPOAE) =f _(DPOAE) _(—) _(BASE) +f(t)  (equation 1)

where f_(DPOAE)=2*f₁−f₂ and f(t) being a modulation function,representing the frequency shift over time.

A different approach would be to shift f1 and f2 by a time varyingfactor:

f ₁ =f _(1BASE) *f(t)

f ₂ =f _(2BASE) *f(t)

f _(DPOAE) =f _(DPOAE) _(—) _(BASE) *f(t)  (equation 2)

where f(t) is the modulation function, usually varying closely around 1.

Other paradigms are possible with the same effect, including paradigmsthat leave one of the primary tones unchanged.

A more general formula would be

f ₁ =f _(1BASE) +f ₁(t)

f ₂ =f _(2BASE) +f ₂(t)

f _(DPOAE) =f _(DPOAE) _(—) _(BASE) +f(t)

with f(t)=2*f₁(t)−f₂(t).

Careful selection of the modulation functions can help optimize thephase behavior of the DPOAE response to allow its proper detection. Iff₂(t)=2*f₁(t), f(t)=0, which is a special case in that the DPOAEresponse is not modulated at all.

Experiments indicate that a sine- or triangle modulation with about ±100Hz frequency shift at 1 Hz modulation rate results in a significantreduction of the fine structure in medium frequencies (2 kHz to 5 kHz).In lower and higher frequencies, parameters can be modified slightly forbest performance. FIGS. 2, 2 a show such a recording. The standardrecording technique for 3 stimulus levels and 3 recordings per settingis shown in FIG. 2 and the FMDPOAE is shown in FIG. 2 a.

Recording Technique

The common method to detect DPOAE is framing the measurement raw data inframes of constant length, with all frequencies (f₁, f₂, f_(DPOAE) beingmultiples of the frame rate).

Repeating Discrete Fourier Transform (DFT) is then applied to the framedaudio data, resulting in a spectrum representation of the data. Framesizes are normally set to powers of 2, to apply a special implementationof the DFT, called Fast Fourier Transform (FFT).

The frames or the FFT components of the frames are usually averaged withsome artifact rejection scheme to finally decide if a DPOAE has beenfound or to determine its amplitude. Alternatively, the frames can beaveraged in time domain and the FFT performed on the averaged resultwith the same result.

Since the primary tone frequencies are picked to be multiples of theframe rates, they and the resulting DPOAE are located at fixed bins ofthe FFT results (spectra). The bin size of the FFT result is equal tothe frame rate, with typical values being in the order of 20 to 50 Hz.

Assuming a frame size of 1,024 samples (a common choice because most FFTalgorithms in use for sound processing require a number of samples be apower of two) gives 512 frequency bands. If we assume a sample rate of44.1 kHz, we have a frequency range of 0 kHz to 22.05 kHz. (Nyquisttheorem is two times the bandwidth of a bandlimited signal or abandlimited channel). The width of each of our frequency bins, which isequal to the frame rate, is determined by the following formula:

bin width=frame rate=Nyquist frequency/number of bins;

giving a bin width of about 43 Hz.

To allow FM modulation of the signal components, this standard methodcannot be used directly. One simple way to do so is to apply frequencymodulation to the sampling frequency of the AD-DA converter. Some AD-DAconverter chips provide such a feature. However, this would be limitedto a modulation as described in equation 2, since all frequencies wouldbe shifted with a common factor.

A more universal modulation range can be achieved if the frequencies areno longer multiples of the frame rates.

This can be achieved with a principle widely used in informationtechnology, called quadrature demodulation or I/Q demodulation.

FIG. 8 is a schematic of one example of how the incoming signal issample per sample multiplied with sine and cosine of the knownf_(DPOAE), resulting in two so-called base band signals (I and Qsignals).

These base band signals can then be windowed, framed, and averaged tocollect the DPOAE signal, represented as a vector in the I/Q plane.Known statistical methods are then applied to decide if a valid responsewas detected. Artifact rejection schemes, such as weighted averaging,can also be applied to this scheme.

The “I” and “Q” signals are windowed, for example with a “raised cosinewindow” (see de.wikipedia.org/wiki/Raised-Cosine-Filter). For eachresulting frame, the “I” and “Q” signal is averaged, resulting in avector for each frame. A frame would typically cover 2048 to 4096samples of data. With a sampling rate of 48 kHz, we would get about 25new vectors per second.

Over frames, the resulting I and Q value for each vector, and I²+Q² areaveraged. This averaging can optionally be done with a weighting factorthat is set lower if much noise is found in a frame and higher if lessnoise is found. A possible noise estimator would be the amplitude resultof band pass filtering the raw data of each frame with a band pass thatis centered at f_(DPOAE).

The results of this averaging are called I_(avg), Q_(avg) and P_(avg)here.

For a statistical evaluation, the averaged values can be evaluated, bycalculating

C=sqrt(I _(avg) ² +Q _(avg) ²)/sqrt(P _(avg)).

This C value can be compared to a given criterion, and if it exceeds avalue of, for example 4, a DPOAE is detected.

Other statistical methods could also be applied to the general signalflow.

This recording and evaluation scheme works with any selection of f₁, f₂,and resulting f_(DPOAE), including FM modulation schemes as describedabove. The frequencies do not need to be multiples of the frame rate andcan be selected to any needed precision, independent of sampling rateand frame size.

Although the described method is primarily directed to a method formeasuring DPOAE with frequency modulated primary tones used for thesuppression of fine structure, it may also be used in conjunction withthe performance of other hearing testing, measurements, and analysiswhere suppression of the fine structure is advantageous.

The method and apparatus described thus provides a new approach formeasuring DPOAE.

DESCRIPTION OF THE DRAWINGS

FIG. 1 is a graph of three recordings performed to prove thereproducibility of the fine structure.

FIG. 2 is a graph of a recording showing the standard recordingtechniques for 3 stimulus levels and 3 recordings per setting.

FIG. 2 a is a graph of a recording showing FMDPOAE demonstrating thesuppression of fine structure for 3 stimulus levels and 3 recordings persetting.

FIG. 3 illustrates a graph of a periodic function, f(t).

FIG. 4 is a graph of the window function w(t).

FIG. 5 is a plot of both the window function, w(t) and function ƒ(t)

FIG. 6 is a plot of ƒ(t)*w(t).

FIG. 7 is a periodicized segment periodically extending the windowedfunction, ƒ(t)*w(t), all along the t-axis.

FIG. 8 is a schematic of the incoming signal sample per samplemultiplied with sine and cosine of the known f_(DPOAE).

FIG. 9 is a circuit control graph.

DESCRIPTION OF THE ILLUSTRATED EMBODIMENTS

FIG. 1 is a graph of three recordings performed to prove thereproducibility of the fine structure.

FIG. 2 is a graph of a recording showing the standard recordingtechniques for 3 stimulus levels and 3 recordings per setting.

FIG. 2 a is a graph of a recording showing FMDPOAE demonstrating thesuppression of fine structure for 3 stimulus levels and 3 recordings persetting.

FIGS. 3 through 7 illustrate the FFT steps. FIG. 3 illustrates a graphof a periodic function, f(t).

FIG. 4 is a graph of the window function w(t).

FIG. 5 is a plot of both the window function, w(t) and function ƒ(t)

FIG. 6 is a plot of ƒ(t)*w(t).

FIG. 7 is a periodicized segment periodically extending the windowedfunction, ƒ(t)*w(t), all along the t-axis.

FIG. 8 is a schematic of the incoming signal sample per samplemultiplied with sine and cosine of the known f_(DPOAE). The commonmethod to detect DPOAE is framing the measurement raw data in frames ofconstant length, with all frequencies (f₁, f₂, and f_(DPOAE) beingmultiples of the frame rates.

The decoding part basically uses the same signal-theory as quadraturedetection. In signal theory, one can “mix down” a signal from somecarrier frequency to a different one. Radios do so, for example a FMtuner “mixes down” the stations RF signal at around 100 MHz to theso-called IF at 10.7 MHz. This makes filtering and amplifying mucheasier, because it only needs to be done at the lower and constant 10.7MHz.

Mixing in this context basically means to multiply the signal with asine signal. In the example of the radio, a “local oscillator” is used,in our example it would generate 110.7 MHz (just 10.7 MHz above thestation we want to receive). The incoming, pre-filtered antenna signalwould be multiplied with this local oscillator signal, and the stationwe want to receive would end up as a 10.7 MHz IF signal for filteringand amplification. In Radio reception, this is also referred to as“heterodyne” principle. (See en.wikipedia.org/wiki/Heterodyn)

Heterodyning is based on the trigometric identity:

${{\sin \; {\theta sin}\; \phi} = {{\frac{1}{2}{\cos \left( {\theta - \phi} \right)}} - {\frac{1}{2}{\cos \left( {\theta + \phi} \right)}}}}\mspace{11mu}$

The product on the left hand side represents the multiplication(“mixing”) of a sine wave with another sine wave. The right hand sideshows that the resulting signal is the difference of two sinusoidalterms, one at the sum of the two original frequencies, and one at thedifference, which can be considered to be separate signals.

Using this trigonometric identity, the result of multiplying two sinewave signals, sin(2πƒ₁t) and sin(2πƒ₂t) can be calculated:

${{\sin \left( {2\pi \; f_{1}t} \right)}{\sin \left( {2\pi \; f_{2}t} \right)}} = {{\frac{1}{2}{\cos \left\lbrack {2{\pi \left( {f_{1} - f_{2}} \right)}t} \right\rbrack}} - {\frac{1}{2}{\cos \left\lbrack {2{\pi \left( {f_{1} + f_{2}} \right)}t} \right\rbrack}}}$

The result is the sum of two sinusoidal signals, one at the sum ƒ₁+ƒ₂and one at the difference ƒ₁−ƒ₂ of the original frequencies

Mixer

The two signals are combined in a device called a mixer. It can be seenfrom the previous section that the ideal mixer would be a device thatmultiplies the two signals. Such devices, called analog multipliers,exist and are used as mixers at lower frequencies, but do not functionwell at the RF frequencies where heterodyning is usually used. However,almost any non-linear electronic component will also multiply signalsapplied to it, producing heterodyne frequencies in its output, so theseare most often used as mixers. A non-linear component is one in whichthe output current or voltage is a non-linear function of its input.Most circuit elements in communications circuits are designed to belinear. This means they obey the superposition principle; if F(ν) is theoutput of a linear element with an input of ν:

F(ν₁+ν₂)=F(ν₁)+F(ν₂)

If two sine wave signals are applied to a linear device, the output isthe sum of the outputs when the two signals are applied separately, withno product terms. So the function F must be non-linear. The onlydrawback to using a non-linear component rather than a multiplier isthat, in addition to the sum and difference frequencies, it producesother unwanted frequency components called harmonics, which must befiltered from the output to leave the desired heterodyne frequency.

Examples of non-linear components that are used as mixers are vacuumtubes and transistors biased near cut-off (class C), and diodes.Ferromagnetic core inductors driven into saturation can also be used. Innon-linear optics, crystals that have non-linear characteristics areused to mix laser light beams to create heterodynes at opticalfrequencies.

Output of a Mixer

To demonstrate mathematically how a non-linear component can multiplysignals and generate heterodyne frequencies, the non-linear function Fcan be expanded in a power series (MacLaurin series):

F(ν)=α₁ν+α_(2ν) ²+α₃ν³+ . . .

To simplify the math, the higher order terms above α₂ will be indicatedby an ellipsis (“. . . ”) and only the first terms will be shown.Applying the two sine waves at frequencies ω₁=2πƒ₁ and ω₂=2πƒ₂ to thisdevice:

ν_(out) =F(A ₁ sin ω₁ t+A ₂ sin ω₂ t)

ν_(out)=α₁(A ₁ sin ω₁ t+A ₂ sin ω₂ t)+α₂(A ₁ sin ω₁ t+A ₂ sin ω₂ t)²+ .. .

ν_(out)=α₁(A ₁ sin ω₁ t+A ₂ sin ω₂ t)+α₂(A ₁ ² sin² ω₁ t+2A ₁ A ₂ sin ω₁t sin ω₂ t+A ₂ ² sin² ω₂ t)+. . .

The second term above contains a product of the two sine waves.Simplifying with trigonometric identities:

$v_{out} = {{\alpha_{1}\left( {{A_{1}\sin \; \omega_{1}l} + {A_{2}\sin \; \omega_{2}t}} \right)} + {\alpha_{2}\left( {{\frac{A_{1}^{2}}{2}\left\lbrack {1 - {\cos \; 2\omega_{1}t}} \right\rbrack} + {A_{1}{A_{2}\left\lbrack {{\cos \left( {{\omega_{1}t} - {\omega_{2}t}} \right)} - {\cos \left( {{\omega_{1}t} + {\omega_{2}t}} \right)}} \right\rbrack}} + {\frac{A_{2}^{2}}{2}\left\lbrack {1 - {\cos \; 2\omega_{2}t}} \right\rbrack}} \right)} + \ldots}$  v_(out) = α₂A₁A₂cos (ω₁ − ω₂)t − α₂A₁A₂cos (ω₁ + ω₂)t + …

So the output contains sinusoidal terms with frequencies at the sumω₁+ω₂ and difference ω₁−ω₂ of the two original frequencies. It alsocontains terms at the original frequencies and at multiples of theoriginal frequencies 2ω₁, 2ω₂, 3ω₁, 3ω₂, etc.; the latter are calledharmonics. These unwanted frequencies, along with the unwantedheterodyne frequency, must be filtered out of the mixer output to leavethe desired heterodyne.

The “multiplier” in a radio can be a tube or transistor, while in ourDPOAE case we simply calculate the product sample by sample.

A special case of this is to “mix down” the signal to zero, or “baseband”. Let our DPOAE be at 2 kHz. We would have a “local oscillator”exactly at 2 kHz, and multiply this sine wave (sample by sample) withthe incoming microphone signal, containing the DPOAE that we look for.

This is done with the original local oscillator signal, and a versionthat is phase shifted by 90°. This procedure is called quadraturedemodulation, but a similar principle is also the core of the Fouriertransform.

In this case, the 2 kHz DPOAE signal would be “mixed down” to frequency0, which means DC. To make this work for all possible phase shiftsbetween our local oscillator and the DPOAE signal, we need the 90°shifted version as well, and end up with the so-called I and Q signals,which in an FFT would be called real and imaginary part. This vectorsignal is then sliced into frames of, say, 2048 samples, windowed toavoid cutting effects, and averaged with some artefact rejectionmechanism (I use “weighted averaging”).

The advantage is, that this detection will also work if the stimulusfrequencies, and with it the DPOAE frequency, are not multiples of theframe rate. They can even change over time (frequency modulation). Theonly important thing is that we must know the DPOAE frequency at alltimes, which we do since it is always following 2*f1−f2. Frequencyshifting must also be done in a way that the DPOAE phase does not “runaway” too far during testing. This somewhat limits modulation depth, butthe exact selection on how to modulate f1 and f2 seems to influence thisphase error, which can therefore be reduced to acceptable values.

In summary, the algorithm needs to support a frequency modulation of thestimuli while still detecting the resulting DPOAE, which will in mostcases also be frequency modulated. Common FFT-based algorithms would notdo so.

In one version of the PC software, it generates plots for longer termmonitoring of OAEs, for monitoring ototoxic effects as well as recoveryfrom ear attacks etc. The scale would be in hours, days or weeks, asneeded, and plot the DPOAE amplitude of certain frequencies, probably ina different color for each frequency. This enables one to easily seewhich frequencies are going up or down in amplitude during treatment orrecovery.

It is a different way of plotting things that already exist for use withthe FMDPOAE to provide better reproducibility, because of the reducedeffect of the fine structure.

This application of the method usually provides better accuracy inlonger term monitoring of OAE amplitudes amid ototoxic treatment,recovery after surgery or other incidents. This is because the finestructure can change during recovery or damage of the inner ear,impacting outcomes of the single measurements. This would in turncorrupt the comparison of DPOAE between tests.

FIG. 9 is a circuit control graph employed by the present invention.

The present invention may be embodied in other specific forms withoutdeparting from its structures, methods, or other essentialcharacteristics as broadly described herein and claimed hereinafter. Thedescribed embodiments are to be considered in all respects only asillustrative, and not restrictive. The scope of the invention is,therefore, indicated by the appended claims, rather than by theforegoing description. All changes that come within the meaning andrange of equivalency of the claims are to be embraced within theirscope.

1. A method for measuring DPOAE by means of frequency modulated stimulicomprising: a. exposing a subject to an incoming signal comprised of twoprimary tones to elicit DPOAE responses, b. frequency-modulating atleast one of the primary tones with modulation function(s) selected toreduce or suppress the generation of DPOAE fine structure, c. recordingthe DPOAE signal, at the known, possibly variable, f_(DPOAE), d.applying a weighted averaging or equivalent scheme to reduce noise inthe recording, and e. applying statistical methods to the DPOAErecording to determine if a valid response was detected and/or estimatethe DPOAE sound level.
 2. A method for measuring DPOAE according toclaim 1, wherein the method is used for newborn hearing screening.
 3. Amethod for measuring DPOAE according to claim 1, wherein the method isused for diagnostic DPOAE measurements.
 4. A method for measuring DPOAEaccording to claim 1, wherein the method is used for estimating thehearing threshold and/or calculation of hearing aid fitting parameters5. A method for measuring DPOAE according to claim 1, wherein the methodis used for long-term monitoring of DPOAE by comparing measurementstaken over hours to weeks, to be used for medical recovery processes orfor monitoring ototoxic effects.
 6. A method for measuring DPOAEaccording to claim 1, wherein frequency modulated primary tones are usednot only for the suppression of fine structure, but in conjunction withthe performance of other hearing testing, measurements, and analysis. 7.A method for measuring DPOAE according to claim 6, wherein the method isused for measuring contralateral suppression of DPOAE.
 8. A method formeasuring DPOAE according to claim 1, wherein statistical method toreject environmental noise artifacts comprises weighted averaging.
 9. Amethod for measuring DPOAE according to claim 1, wherein quadraturedemodulation is used to detect DPOAE signals.
 10. A method for measuringDPOAE according to claim 9, including: a. calculating the I and Qcomponents of the quadrature signal by multiplying the incoming (raw orpre-filtered) signal with appropriate sine and cosine functions, b.windowing and framing the I and Q data is independently, c. averagingthe I and Q signals with optional weighting, d. statistically evaluatingthe averaged I/Q vector to detect a statistically significant DPOAEsignal and/or estimate its amplitude.
 11. An apparatus for measuringDPOAE by means of frequency modulated stimuli comprising: a. means forexposing a subject to an incoming signal comprised of two primary tonesto elicit DPOAE responses, b. means for frequency-modulating at leastone of the primary tones with modulation function(s) selected to reduceor suppress the generation of DPOAE fine structure, c. means forrecording the DPOAE signal, at the known, possibly variable, f_(DPOAE),d. means for applying a weighted averaging or equivalent scheme toreduce noise in the recording, and e. means for applying statisticalmethods to the DPOAE recording to determine if a valid response wasdetected and/or estimate the DPOAE sound level.